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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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reduced-order models; integrate the resulting methods with an existing coupled floating-platform code; and verify and validate the models using suitable numerical, experimental and field data. They will
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mathematical models to address fundamental questions in biology. Examples of research topics include but are not limited to: development of new AI architectures for biology and hybrid models that combine deep
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to immediately save millions of pounds, and to be deployed to reservoirs in the UK and beyond. We are looking for a well-motivated individual, with a good technical background including numerical modelling and
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modelling activity. Demonstrated expertise in finite-element methods or related numerical techniques. Experience in code development, HPC architectures, and parallel programming is highly desirable
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methods that extend current sets of flood scenarios derived from physical and numerical models, incorporate climate change effects, and then use these enriched datasets to assess the future insurability of
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increasingly sophisticated representations of marine biogeochemical processes and unprecedented high-resolution numerical experimentation. Together, they will help ensure that the modelling infrastructure
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of stress intensity factor evolution at the crack tip. Concurrently, a numerical model will be developed to complement the experimental results and allow for the calculation of crack propagation rates. Work
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exposed to severe weather events, whose predictability is strongly limited by numerous factors: the complexity of the orography and land use, the presence of mountain— coast—sea transition zones, and the
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physics, quantum optics, exciton–polaritons, light–matter interaction, numerical simulations, or quantum modelling is meritorious. Willingness to work in an inter-cultural, international, and diverse group